Summary: Geometry Refinement of 3D Surfaces Using Kriging
Brad Grinstead, Andreas Koschan, and Mongi A. Abidi
Imaging, Robotics, and Intelligent Systems Laboratory
The University of Tennessee
{bgrinste, akoschan, abidi} @utk.edu
Abstract
3D imaging is a popular method for acquiring
accurate models for a variety of applications.
However, the size of the geometric features that can be
modeled in this manner is dependant on the scanning
system's resolution. This paper presents a method
that attempts to accurately reconstruct regions whose
features are at or below the system's scanning
resolution, combining automatic region selection with
a form of kriging. A curvature-based segmentation is
followed by an automated geometry refinement
procedure in which the model of spatial correlation
between the irregularly sampled 3D data is
automatically determined. Geometry refinement is
done by a regularized kriging approach that is